In June 2020 MIT withdrew Tiny Imageshttps://groups.csail.mit.edu/vision/TinyImages/, 2020/07/10. a popular vision dataset as researchers found that it is socially biased. Biases in training data are a major issue for machine learning algorithms [1]}.
Especially, as they are increasingly used to make critical decisions. First, it is important to ensure that those systems are fair and do not discriminate certain groups. Secondly, interpretability of the decisions - "why" the system comes to that conclusion or how important a certain factor for decision making is - are desirable for better understanding. Thirdly, these trained models should generalize well. For many real world situations the data seen during training is different then the data which the models are applied to in production. Domain adaptation tries to transfer knowledge from a source domain (training set) to a particular target domain. In order to cope with these challenges many different approaches have been proposed over the last decade.
